Mapping the reference genetic network of a eukaryotic cell

绘制真核细胞的参考遗传网络

• 批准号: 8306581
• 负责人: Brenda Jean ANDREWS
• 金额: $ 66.5万
• 依托单位: UNIVERSITY OF TORONTO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-26 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8306581
• 关键词: Address; Amaze; Animal Model; Atlases; Cataloging; Catalogs; Cell Cycle; Cell physiology; Cells; Communities; Complex; Data; Data Set; Databases; Development; Disease; Distant; Drug Delivery Systems; Eukaryota; Eukaryotic Cell; Evolution; Fission Yeast; Foundations; Future; Genes; Genetic; Genetic Variation; Genome; Genomics; Genotype; Goals; Grouping; Health; Human; Link; Mammalian Cell; Mammalian Genetics; Maps; Methods; Modeling; Nobel Prize; Organism; Pathway interactions; Phenotype; Research; Resources; Saccharomyces cerevisiae; Saccharomycetales; Sequence Analysis; Surveys; Testing; To specify; Work; Yeasts; base; bioprocess; comparative; computerized tools; functional genomics; gene function; genetic analysis; genome sequencing; human disease; insight; man; meetings; mutant; programs; public health relevance; tool; web-accessible; yeast genetics

DESCRIPTION (provided by applicant): The importance of genetic interactions in disease has been emphasized by genome sequencing projects which have revealed the astounding genetic diversity in a variety of organisms, from yeast to man. We are now faced with the significant challenge of assigning functions to the thousands of uncharacterized genes, and how to use this information to understand how genes interact to determine cell function in health and disease. Despite amazing technical advances, our understanding of genetic interactions relevant to human disease remains rudimentary, and discovering relevant interactions demands an integrated, systematic approach. The proposed work aims to address this challenge by identifying genetic interactions in a model eukaryote, the budding yeast, Saccharomyces cerevisiae. We developed the Synthetic Genetic Array (SGA) method which automates yeast genetics and enables systematic analysis of genetic interactions. 'The emerging principles of genetic networks suggest that systematic identification of genetic interactions offers the potential to organize genomes into hierarchical maps, grouping genes into coherent pathways. This project will complete a reference genetic interaction map for the eukaryotic cell and will explore the conservation of genetic networks over millions of years of evolution. A complete atlas of genetic interactions will reveal how genes act in concert to specify the cellular programs that control development, differentiation, and disease states. AIM 1: Mapping the reference genetic interaction network. The SGA approach will be used to complete the genetic interaction network map for the budding yeast, a fundamental eukaryotic cell that shares thousands of genes and the basic cellular functions of its human counterparts. The complete genetic interaction "altas" in yeast will guide development of the first mammalian genetic interaction maps. AIM 2: Surveying genetic interactions in fission yeast. Fission yeast is a model organism that is separated from budding yeast by hundreds of millions of years of evolution. Comparison of genetic interactions between these two unicellular organisms will provide a foundation for understanding genetic networks in human cells. AIM 3: Database and Computational Tools for Cross-Species Analysis of Genetic Interactions. We will develop a web-accessible data warehouse for storage and cross-species analysis of genetic interaction networks. A cross-species database will enable analysis of the general rules governing conservation or rewiring of interactions and prediction of conserved interactions. PUBLIC HEALTH RELEVANCE: This project will produce unique datasets and tools that will reveal how genes interact in normal and diseased cells. Genetic interaction reference maps produced by the project will provide valuable insights into gene function, drug target analysis and the link between genotype and phenotype, including the genetic basis of human disease.

描述(由申请人提供)：基因组测序项目强调了疾病中遗传相互作用的重要性，这些项目揭示了从酵母到人类的各种生物中惊人的遗传多样性。我们现在面临着一个重大的挑战，即如何为数以千计的未确定特征的基因分配功能，以及如何利用这些信息来理解基因如何相互作用来决定健康和疾病中的细胞功能。尽管技术取得了惊人的进步，但我们对与人类疾病相关的基因相互作用的理解仍然处于初级阶段，发现相关的相互作用需要一种综合的、系统的方法。这项拟议的工作旨在通过确定模式真核生物--萌芽酵母--酿酒酵母中的基因相互作用来应对这一挑战。我们开发了合成遗传阵列(SGA)方法，它使酵母遗传学自动化，并使遗传相互作用的系统分析成为可能。“遗传网络的新兴原理表明，对遗传相互作用的系统识别提供了将基因组组织成分层图谱、将基因分组成连贯路径的可能性。”该项目将完成真核细胞的参考遗传相互作用图，并将探索数百万年进化过程中遗传网络的保护。一份完整的遗传相互作用图谱将揭示基因如何协同作用，以指定控制发育、分化和疾病状态的细胞程序。目的1：定位参考遗传互作网络。SGA方法将用于完成发芽酵母的遗传相互作用网络图，发芽酵母是一种基本的真核细胞，共享数千个基因和人类同行的基本细胞功能。酵母中完整的遗传相互作用“Altas”将指导第一个哺乳动物遗传相互作用图谱的开发。目的2：研究分裂酵母中的遗传交互作用。分裂酵母是一种模式生物，经过数亿年的进化从萌芽酵母中分离出来。比较这两种单细胞生物之间的遗传相互作用将为理解人类细胞中的遗传网络提供基础。目标3：遗传相互作用跨物种分析的数据库和计算工具。我们将开发一个可通过网络访问的数据仓库，用于遗传相互作用网络的存储和跨物种分析。跨物种数据库将能够分析关于相互作用的保护或重新连接的一般规则，以及对保守的相互作用的预测。 与公共健康相关：该项目将产生独特的数据集和工具，揭示基因如何在正常和疾病细胞中相互作用。该项目制作的遗传相互作用参考图将为基因功能、药物靶标分析以及基因和表型之间的联系提供有价值的见解，包括人类疾病的遗传基础。